Autonomous Precision Manipulation

In our manipulation work (Michelman and Allen [6][9][8]), we investigate the requirements
and implementation of precision tasks, in which ``precision tasks'' are
defined as those in which the motions of grasped objects are caused by
fingertip motions alone. The motivation for this work has been the
development of strategies that will enable hands to perform precision tool
tasks which require the control of interaction forces between the grasped
object and the environment.

A set of primitive manipulations is defined,
encompassing six fundamentally different techniques. Each manipulation
defines a basic translation or rotation of an object with either circular or
rectangular cross section and can be performed with a number of different
grasp configurations. Taken together, the set of primitives enables the hand
to rotate or translate objects in any direction in an object-centered frame.
Defining basic strategies, an analog to motor control programs, simplifies the
planning requirements of a robot system. Once a high-level planner has
decided that a particular object motion is required, the action is performed
autonomously. Manipulations are parametrized to cope with different task
requirements, including grasp force, motion distance, and speed. It is
assumed that the tasks are performed slowly enough to require quasistatic
analysis, that the objects are rigid (though a precise object model is not
required), and that force and position control are available. The elements of
the tasks are: (1) a description of fingertip trajectories, (2) an analysis of
the hand's workspace, (3) a method of maintaining grasp stability during
manipulation, for which hybrid force/position control is used for task
partitioning. Trajectories define the finger contact motions during
manipulation. A hand's workspace is generally complex and does not admit a
closed-form solution. For object manipulation, allowable fingertip
trajectories for all contacts must be found simultaneously. A
configuration-space analysis is performed that yields the maximum object
motion distance for given sized objects, as well as the initial grasping
positions and wrist positions in a global frame. This information is required
to position the robot arm for maximum object manipulability, that is, to move
it during the reach phase of a manipulation. Task partitioning, the
specification of force- and position-controlled directions, simplifies the
maintenance of grasp forces during manipulation and often yields a
straightforward method to control the external object forces.

A number of experiments have been performed with a Utah/MIT hand system. In
addition to the elementary tasks (2-D translations and rotations), complex
tasks involving sequential manipulations (for example, removing the top of a
child-proof bottle and rotating a rectangular block) have been analyzed.
These complex tasks often involve extending the elementary motor-control
programs to include task-specific requirements and suggest limits to the
generalizability of such motor control programs.

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